| Title: |
Emergent motion capture technology for upper extremity assessment in stroke: A systematic scoping review |
| Authors: |
Fisher, J; Makroglou, K; Tinker, J; Shiner, CT; Hurden, A; Weston, J; Li, L; Rauniyar, C; Lannin, NA; Anderson, CS; Chen, X |
| Source: |
urn:ISSN:0269-2155 ; urn:ISSN:1477-0873 ; Clinical Rehabilitation, 54, SUPPL 2, 2692155261420748 |
| Publisher Information: |
SAGE Publications |
| Publication Year: |
2026 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
42 Health Sciences; Brain Disorders; Stroke; Bioengineering; Cerebrovascular; Neurosciences; assessment; kinematics; motion capture; rehabilitation; technology; upper limb; anzsrc-for: 42 Health Sciences; anzsrc-for: 11 Medical and Health Sciences; anzsrc-for: 32 Biomedical and clinical sciences |
| Description: |
Objective: To systematically appraise motion capture technologies used for clinical assessment of upper limb function in adults post stroke, focusing on applicability, strengths, limitations, and research gaps. Data Sources: A systematic scoping review was conducted in accordance with PRISMA-ScR guidelines. PubMed, MEDLINE, CINAHL, CENTRAL, and IEEE Xplore were searched for studies published between January 2014 and December 2025. Review Methods: Eligible studies quantitatively evaluated motion capture systems in adult stroke populations. Data extracted included technology type, technical specifications, outcomes, and reported strengths and limitations. Results: From 3217 screened studies, 204 were included. Inertial measurement units were most common (71) followed by markerless optical motion capture (43), electromyography (39), marker-based optical motion capture (33), fusion systems (10), and smart devices (8). Marker-based systems provided high precision but were costly and complex. Markerless systems reduced setup requirements and supported clinical use but were prone to tracking errors. Inertial measurement units enabled portable monitoring, though accuracy decreased for slow or fine movements. Electromyography offered insights into neuromuscular activity but was expensive and sensitive to placement. Fusion systems allowed multidimensional assessment but were resource intensive. Smart devices provided accessible options but lacked precision. Most studies focused on chronic stroke, with limited evaluation in acute or home contexts. Reporting of stroke severity was inconsistent, and protocols were rarely standardised. Conclusion: Motion capture technologies show promise for upper limb assessment after stroke but face challenges of cost, accessibility, and standardisation. Research in acute and home settings, along with predictive modelling, is needed to support clinical translation. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/107990; https://doi.org/10.1177/02692155261420748 |
| DOI: |
10.1177/02692155261420748 |
| Availability: |
https://hdl.handle.net/1959.4/107990; https://unsworks.unsw.edu.au/bitstreams/455dd350-cac9-44df-bdcc-23f1d0da8e78/download; https://doi.org/10.1177/02692155261420748 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; No Licence ; free_to_read |
| Accession Number: |
edsbas.C1F7F8DC |
| Database: |
BASE |